We are seeking a Data Analyst responsible for Analyze, create, maintain, and review complex objects and data models to align with project requirements. This role focuses on source-to-target data mappings, SQL-based data analysis and validation, data quality monitoring, and collaboration with customers and internal teams to support technology-enabled business projects.
Analyze, create, maintain, and review complex objects and data models to align with project requirements.
Complete source-to-target data mappings with detailed transformations to be used by developers in writing code.
Write SQL to analyze, validate, or correct data according to project requirements, including complex stored procedures, views, and functions.
Measure and monitor data quality, review data issues, perform analysis, and execute remediation plans according to company standards and procedures.
Provide oversight and direction for the team to develop solution alternatives and recommendations for technology-enabled business projects.
Review recommendations and present findings to the business, data analysts, integration teams, BI Services, and other stakeholders as appropriate for direction and decision-making.
Perform review of deliverables and artifacts for projects and require any misalignment, quality, or compliance issues to be corrected.
Research, evaluate, and recommend software packages and solutions for purchase and deployment.
Participate in the hiring process as needed.
Proficient in data modeling for both transactional and dimensional data warehouse databases.
Proficient in the creation of source-to-target mappings, including mapping of tables, files, and XML schemas from source to target.
Working experience with a standard data modeling toolset; working knowledge of ER/Studio is a strong plus.
Data mining skills, including data auditing, aggregation validation, and reconciliation.
Strong ability with SQL Server and Azure databases such as Fabric Lakehouse and Synapse.
Data analysis experience with data profiling and data validation.
Data quality understanding of DQ concepts and familiarity with DQ tools and methods.
Experience communicating with customers to obtain data requirements and perform data analysis on data provided.
Working knowledge of Hadoop platforms and data components such as Hive, HBase, or Impala.
Knowledge of real-time analytics and BI platforms such as Tableau.
Strong oral and written communication and presentation skills.
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